Dr. Noyes proposes to develop the skills necessary to become an independent researcher in the field of cost-effectiveness analysis and health policy evaluation in geriatric disease. The candidate's undergraduate training in biomedical physics and PhD training in neurophysiology confirm her commitment to research as well as her strong analytical capabilities. To strengthen her knowledge in health care policy, outcomes evaluation, statistical analysis, and data management, the candidate will complete the proposed didactic coursework and participate in a series of clinical skills workshops and seminars. The candidate will spend the main part of the five-year grant period conducting proposed research. The candidate's long-term plan is to improve efficiency of the health care system by incorporating cost-effectiveness analysis into health care policy and decision making, in particular, related to Parkinson's disease (PD) and geriatric depression. The study will address short-comings of the methods currently used to evaluate outcomes in PD and will use patient's quality of life as the effectiveness measure. It is hypothesized that 1) levodopa is more cost-effective than pramipexole in the treatment of early PD; 2) elderly chronically ill patients use more health services than do general Medicare beneficiaries; and 3) disability and long-term care are the main sources of expenses associated with chronic geriatric disease. The project's specific aims are to conduct a cost-effectiveness analysis of early PD therapy with pramipexole compared to levodopa, to assess the pattern of health care utilization in Medicare beneficiaries with PD, and to develop a Parkinson's disease health policy pilot model. The cost-effectiveness will be assessed based on 4 years of data collected from a clinical-economic trial in PD. The patterns of health services utilization of Medicare patients will de examined using the Medicare Current Beneficiary Survey. Supplemental data on costs will be collected from published literature and Medicare fee schedules. The study design will include cost-effectiveness analysis, decision analytical modeling, sensitivity analysis, and Bayesian statistics. The results of this study can serve as a foundation for developing clinical guidelines for PD, provide information for resource allocation with respect to long term institutional and informal care, and to improve public health policy associated with chronic diseases and aging. Supervision for this project will be provided by a multidisciplinary team at the University of Rochester whose members are experienced in fostering the development of clinical researchers. The model and analytical approaches acquired by the candidate during her training will be used later to develop a decision analytical model describing geriatric depression.